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DOE OSTI2024

Inertia Estimation and Trend Analysis of the United States Power Grid Interconnections

The transition from conventional to modern power systems is causing an increase in integration of inverter-based resources (IBRs). This generally leads to a decrease in total system inertia, which in-turn increases the system’s rate-of-change-of-frequency (RoCoF) during disturbances. This poses a threat to the frequency stability of the system and may falsely trigger protective devices. To monitor system status and plan for integrating renewable energy sources like photovoltaic, wind, and energy storage systems, a realistic study of inertia estimation and analysis in the United States (US) over the past decade is needed. This paper uses field-measured phasor measurement unit (PMU) data collected throughout the US from 2013 to 2023 via the Frequency Monitoring Network (FNET/GridEye) operated by the University of Tennessee, Knoxville (UTK) and Oak Ridge National Laboratory (ORNL). The collected PMU frequency data is utilized to estimate the system inertia of the three US interconnections: Eastern, Western, and Texas. Various RoCoF time windows are investigated for estimating the inertia of each interconnection by maximizing the correlation coefficient between the measured RoCoF and power mismatch. The resulting inertia trends over the past decade show approximately a 6% decline in inertia in the Eastern interconnection, a 15% decline in inertia in the Western interconnection, and a 16% increase in inertia in Texas. Key insights into how inertia is changing amidst the complex energy landscape are extracted using the fuel mix trend data. This provides valuable information for future energy strategies and planning.

30 DIRECT ENERGY CONVERSION↗

NASA NTRSDate not supplied

Two-Phase Flow in Filters and Orifices: ISS Packed Bed Reactor Experiment Water Recovery Series (PBRE-WRS)

Understanding the hydrodynamics of adiabatic two-phase flows in packed bed reactors offers numerous benefits. It enables the optimization of chemical reactions rates and products which results in more efficient and compact reactors, thus reducing space and resource requirements, crucial for long duration space missions. The Packed Bed Reactor Experiment-Water Recovery Series (PBRE-WRS) is a flight experiment planned for operation on the Microgravity Science Glove box (MSG) facility of the International Space Station (ISS). The objective of the experiment is to validate hydrodynamic models at a range of gas and liquid flow rates, where these models are used in the design of processes for life support systems in microgravity. The microgravity environment allows for measurement and observation of aspects of fluid dynamics that are unique when compared to observations made in full or partial gravity environments. The experiment consists of testing two-phase flow hydrodynamics in three different filters, four (4) orifices and one check valve test articles. The experiment utilizes the hardware of the previously flown PBRE and PBRE-2 with packed beds of different packings materials and sizes. The fluid system of the PBRE-WRS consists of a nitrogen gas delivery and water delivery subsystems. The gas delivery subsystem can accommodate two ranges of gas flow rates, just as for the water delivery system. The nitrogen gas loop is open whereas the water loop is closed. Gas is separated from the water using a gas-liquid phase separator which is located in the water delivery module. Preliminary results from ground testing show the pressure drop across the filters increasing at different rates with the liquid and gas flow rates. In this work, a detailed system description is presented along with a summary of results from ground performance testing of different test sections in an end-to-end preflight testing campaign.

ISS↗

DOE OSTI2020

Survey and Assessment of the Ocean Renewable Energy Resources in the US Gulf of Mexico

This study was conducted by the National Renewable Energy Laboratory (NREL) and funded by the Bureau of Ocean Energy Management (BOEM). It provides a comprehensive feasibility assessment of multiple offshore renewable energy technologies in the Gulf of Mexico (GoM) to inform BOEM's strategic plans related to possible Outer Continental Shelf alternative energy leasing activities in the GoM. In coordination with Gulf Coast states, the study includes some information on offshore renewable energy potential in state waters for future energy planning. The goal of the study is to survey potential offshore renewable energy sources in the GoM and quantify their feasibility relating to resource adequacy, technology maturity, and the potential for competitive cost. The study provides a review of available technologies and concepts for generating offshore renewable energy, including a high-level assessment of the current state of each technology and its potential for future advances. It provides a breakdown of resource capacity for each renewable energy technology and a recommendation that offshore wind be pursued for future study as the most promising technology. The renewable technologies that were considered include offshore wind, wave energy, tidal energy, ocean current energy, offshore solar energy, ocean thermal energy conversion (OTEC), cold water source cooling, and hydrogen (as a storage medium to utilize existing pipeline infrastructure). The resource capacity for each of these renewable energy sources was quantified for both the gross resource capacity potential (gross resource) and the technical resource capacity potential (technical resource) using the methodology described in an earlier NREL report. Many of these sources are very immature from a commercial perspective, which makes some of the comparisons difficult. In many cases, new methods were developed to estimate nominal power density for each technology type, which were necessary to convert the resource areas into deployable gross and technical resource capacity potentials.

17 WIND ENERGY↗

DOE OSTI2023

State Energy Justice Roundtable Series: Participation in Decision Making

The National Association of Regulatory Utility Commissioners (NARUC), National Association of State Energy Officials (NASEO), and National Governors Association (NGA) hosted a State Energy Justice Roundtable (Roundtable) in April 2022. Participants included federal and state decision-makers, members of community-based organizations, and subject-matter experts. The Roundtable members explored current state efforts to articulate and incorporate energy justice concerns into energy-related decision-making. Participants established connections with one another to better understand the current landscape of existing resources, learn about emerging efforts, and identify ongoing support opportunities for advancing energy justice.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Reduced Contracting Time To Accelerate Construction: A Streamlined Approach for Speed and Scale

In the fast-paced construction world, efficiency isn't just an advantage - it's a necessity. By implementing the Cooperative Construction Contracting Agreement (CCCA), we are transforming how we approach major projects, replacing traditional multistep contracting with a streamlined, one-step process. This innovative contracting approach saves valuable time and resources, enabling us to accelerate delivery across our portfolio of projects. Under the old model, each construction phase required separate competitive solicitations for design, build, and other services. With the CCCA, we've consolidated these steps, working with a trusted partner from start to finish. This results in significant time savings that translate into faster project execution without compromising quality or safety.

collaborative partnerships↗

NASA NTRS1984

Satellite Precipitation and Cloud Experiment (SPACE)

An experiment plan was formulated to support an investigation of the precipitation processes associated with mesoscale systems and the interaction of rain producing cloud complexes with the meso and macro-scale environment. The field program necessary to accomplish the scientific goals is designed to incorporate satellite information (VIS and IR as well as VAS data), special radiosonde and surface observing capabilities, radar observations of storms development, special observations from aircraft and ground based lightning measurements. The observing network comprises rawinsonde stations located in northern Alabama and eastern Tennessee. A high density raingauge network and the MSFC lightning location network also cover the area. Coordination with NASA U2 and ER2 aircraft programs and with the operational requirements of the microburst severe thunderstorm program can assure the most efficient utilization of the observing resources.

Arnold, J. E.↗

NASA NTRS2009

Emittance Measurements Relevant to a 250 W(sub t) Class RTPV Generator for Space Exploration

A proposed 250 Wt Radioisotope Thermophotovoltaic (RTPV) power system for utilization in lunar exploration and the subsequent exploration of Mars is described. Details of emitter selection are outlined for use in a maintenance free power supply that is productive over a 14-year mission life. Thorough knowledge of a material s spectral emittance is essential for accurate modeling of the RTPV system. While sometimes treated as a surface effect, emittance involves radiation from within a material. This creates a complex thermal gradient which is a combination of conductive and radiative heat transfer mechanisms. Emittance data available in the literature is a valuable resource but it is particular to the test sample s physical characteristics and the test environment. Considerations for making spectral emittance measurements relevant to RTPV development are discussed. Measured spectral emittance data of refractory emitter materials is given. Planned measurement system modifications to improve relevance to the current project are presented.

Wolford, Dave↗

DOE OSTI2025

A sequential Attacker-Defender game for distribution systems resilience enhancement against extreme weather events

Improving distribution system resilience against frequent extreme weather events is important for reliable power system operations. Especially when dealing with events such as hurricanes that have short-term predictions, proactive pre-event preparedness plays a vital role in system resilience performance. In this paper, we propose a novel approach to construct pre-event resource allocation plans for system operators to cope with upcoming threats through a sequential attacker-defender game framework. The sequential attacker-defender game is designed to model the interaction between the extreme weather and the system operator. In each round of the game, the attacker and the defender sequentially update their current strategies by accounting for the opponent’s action set. The attacker model is formulated as a bi-level problem to identify the severe outage scenarios, and the defender model is formulated as a two-stage optimization problem to determine the allocation of restoration resources including mobile responsive resources and repair crews. Two scale-reduction strategies are proposed to ensure the scalability of the game scheme. Finally, case studies on the IEEE 33-bus and a 7149-node practical utility system validate the effectiveness of the proposed sequential game and the efficiency of the scale-reduction strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Beneficial Integration of Energy Storage and Load Management with Photovoltaic (PV)

In recent years, a number of industry activities have aimed at addressing the integration challenges posed by the variability and uncertainty of higher penetration of renewable generation sources, like solar photovoltaic (PV) – one of the key objectives of the Sustainable and Holistic Integration of Energy Storage and Solar PV (SHINES) program launched by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). This EPRI led Beneficial Integration of Energy Storge, and Load Management with PV project aimed to design, develop, and demonstrate end-to-end distributed energy resource (DER) integration solution to build on these activities. EPRI led project team designed and implemented a local controller that uses model predictive control (MPC) algorithm to optimally manage DERs on site by planning for a receding horizon while executing the control settings for the first step of its plan. The team has also developed a system controller to interface with the local controller to demonstrate the hierarchical control and how it can leverage DER capabilities to address challenges like over voltage and thermal limit violations which typically limits the DER hosting capacity of distribution feeders. Team has demonstrated how the local controller with optimization algorithm can effectively manage controllable loads like HVAC, water heater, and pool pumps to allow for greater integration of PV with relatively smaller energy storage system requirements. Optimal utilization of the load control can also reduce the depth of discharge of batteries to meet grid export/import limit from behind-the-meter (BTM) DERs. Proper utilization of DER capabilities via local control intelligence, like the one developed and demonstrated in this project can help the industry to address integration challenges of higher penetration of solar PV in economically efficient manner. This can help to accelerate deployment of clean renewable energy systems at lower societal cost.

14 SOLAR ENERGY↗

NASA NTRS1985

To catch a childs's imagination: Educational overview of CAN DO G-324

When a public school district is involved in the flight of a GAS package, they have a The desire to produce an serious responsibility, along with an unprecedented opportunity. experiment with real scientific validity must be tempered by the schools' primary mission to make the adventure educationally meaningful to the greatest possible number of students. Such a project can easily become the personal plaything of the select few that are highly scientifically motivated, and technologically gifted. A public school system must, in addition, insure that the resources invested in such a project also reach out to the average student, and those whose interests lie in other directions. Such a broad reach is only possible if the GAS canister is but one part of a comprehensive and ongoing educational effort that involves as many disciplines and levels of student interest as possible. The total program should include: 1) A background of previous programs which have trained teachers and prepared students to fully utilize special activities as part of the educational process. 2) Direct student involvement in the design of experimental packages to be flown, and in the evaluation of data derived. 3) Supplementary related activities that use a Get Away Special as a motivational catalyst to generate efforts in other disciplines, other schools and other student groups. 4) Future plans to fully exploit and maintain the momentum developed by this one dramatic event. The one overriding goal of all these activities as articulated by one of our leading classroom teachers: "TO CHOOSE AND DEVELOP HIGHLY MOTIVATION& ACTIVITIES WHICH WILL CAPTURE THE IMAGINATION AND INTEREST OF STUDENTS, AND TO TAKE ADVANTAGE OF THE "TEACHABLE MOMENT" WHICH IS SO ELUSIVE."

James H. Nicholson↗

NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗

DOE OSTI2020

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids with Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2009

Lunar Mapping and Modeling Project

The Lunar Mapping and Modeling Project (LMMP) has been created to manage the development of a suite of lunar mapping and modeling products that support the Constellation Program (CxP) and other lunar exploration activities, including the planning, design, development, test and operations associated with lunar sortie missions, crewed and robotic operations on the surface, and the establishment of a lunar outpost. The project draws on expertise from several NASA and non-NASA organizations (MSFC, ARC, GSFC, JPL, CRREL and USGS). LMMP will utilize data predominately from the Lunar Reconnaissance Orbiter, but also historical and international lunar mission data (e.g. Apollo, Lunar Orbiter, Kaguya, Chandrayaan-1), as available and appropriate, to meet Constellation s data needs. LMMP will provide access to this data through a single, common, intuitive and easy to use NASA portal that transparently accesses appropriately sanctioned portions of the widely dispersed and distributed collections of lunar data, products and tools. LMMP will provide such products as DEMs, hazard assessment maps, lighting maps and models, gravity models, and resource maps. We are working closely with the LRO team to prevent duplication of efforts and ensure the highest quality data products. While Constellation is our primary customer, LMMP is striving to be as useful as possible to the lunar science community, the lunar education and public outreach (E/PO) community, and anyone else interested in accessing or utilizing lunar data.

Noble, Sarah K.↗

NASA NTRS2016

Resource Prospector Instrumentation for Lunar Volatiles Prospecting, Sample Acquisition and Processing

Data gathered from lunar missions within the last two decades have significantly enhanced our understanding of the volatile resources available on the lunar surface, specifically focusing on the polar regions. Several orbiting missions such as Clementine and Lunar Prospector have suggested the presence of volatile ices and enhanced hydrogen concentrations in the permanently shadowed regions of the moon. The Lunar Crater Observation and Sensing Satellite (LCROSS) mission was the first to provide direct measurement of water ice in a permanently shadowed region. These missions with other orbiting assets have laid the groundwork for the next step in the exploration of the lunar surface; providing ground truth data of the volatiles by mapping the distribution and processing lunar regolith for resource extraction. This next step is the robotic mission Resource Prospector (RP). Resource Prospector is a lunar mission to investigate 'strategic knowledge gaps' (SKGs) for in-situ resource utilization (ISRU). The mission is proposed to land in the lunar south pole near a permanently shadowed crater. The landing site will be determined by the science team with input from broader international community as being near traversable landscape that has a high potential of containing elevated concentrations of volatiles such as water while maximizing mission duration. A rover will host the Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) payload for resource mapping and processing. The science instruments on the payload include a 1-meter drill, neutron spectrometer, a near infrared spectrometer, an operations camera, and a reactor with a gas chromatograph-mass spectrometer for volatile analysis. After the RP lander safely delivers the rover to the lunar surface, the science team will guide the rover team on the first traverse plan. The neutron spectrometer (NS) and near infrared (NIR) spectrometer instruments will be used as prospecting tools to guide the traverse path. The NS will map the water-equivalent hydrogen concentration as low as 0.5% by weight to an 80 centimeter depth as the rover traverses the lunar landscape. The NIR spectrometer will measure surficial H2O/OH as well as general mineralogy. When the prospecting instruments identify a potential volatile-rich area during the course of a traverse, the prospect is then mapped out and the most promising location identified. An augering drill capable of sampling to a depth of 100 centimeters will excavate regolith for analysis. A quick assay of the drill cuttings will be made using an operations camera and NIR spectrometer. With the water depth confirmed by this first auguring activity, a regolith sample may be extracted for processing. The drill will deliver the regolith sample to a crucible that will be sealed and heated. Evolved volatiles will be measured by a gas chromatograph-mass spectrometer and the water will be captured and photographed. RP is a solar powered mission, which given the polar location translates to a relatively short mission duration on the order of 4-15 days. This short mission duration drives the concept of operations, instrumentation, and data analysis towards critical real time analysis and decision support. Previous payload field tests have increased the fidelity of the hardware, software, and mission operations. Current activities include a mission level field test to optimize interfaces between the payload and rover as well as better understand the interaction of the science and rover teams during the mission timeline. This paper will include the current status of the science instruments on the payload as well as the integrated field test occurring in fall of 2015. The concept of operations will be discussed, including the real time science and engineering decision-making process based on the critical data from the instrumentation. The path to flight will be discussed with the approach to this ambitious low cost mission.

ISRU↗

NASA NTRS2020

Apollo Next Generation Sample Analysis (ANGSA): A Segue to the Next Era of Lunar Exploration and Sample Return Activities

In the fifty years since the first lunar samples were collected on Apollo 11, significant advancements have taken place in laboratory analysis, planetary science, and astromaterials curation. These advances are now being leveraged for the Apollo Next Generation Sample Analysis (ANGSA) Program, which aims to study specially curated Apollo samples that have never been studied before. Since Apollo 17 in 1972, a great deal has been learned about the Moon, including the unique environments of the poles. Building upon Apollo and remote sensing studies since then, the Artemis Program aims to explore the cold environments near the lunar south pole while achieving the concurrent goals of landing the first woman and the next man on the Moon by 2024. Recent developments for ANGSA have significantly accelerated our readiness for Artemis sample return, particularly in the area of cold sample studies. Four science teams were selected to study cold and/or volatile-bearing samples collected during the Apollo program. These samples have special storage and handling requirements that necessitate their processing in a -20°C environment that meets the Apollo materials and cleanliness requirements. NASA has recently undertaken the development and implementation of a cold sample processing facility to support ANGSA. A similar facility will be needed to process the cold, volatile-bearing samples planned to be returned by Artemis missions; therefore, ANGSA provides excellent preparation for Artemis’ future cold sample processing efforts. We will outline the goals of the ANGSA and Artemis programs, illustrating the complementary nature of the work for both. We will describe the efforts to date in designing, testing, and implementing a cold curation facility that meets the requirements of ANGSA and Apollo curation. We will then outline future work for that facility to reach operational readiness. Finally, we will present the sample collection and curation strategies for Artemis, showing how they overlap and build on ANGSA efforts. The development of cold curation at NASA represents a significant leap in the knowledge, experience, and technologies used in astromaterials curation, opening the door for new investigations of lunar volatiles, impacts, formation processes, prebiotic chemistry, and resource utilization, among many others.

Julie Mitchell↗

NASA NTRS2020

Exploring Spatiotemporal Relations Between Soil Moisture, Precipitation, and Streamflow for a Large Set of Watersheds Using Google Earth Engine

An understanding of streamflow variability and its response to changes in climate conditions is essential for water resource planning and management practices that will help to mitigate the impacts of extreme events such as floods and droughts on agriculture and other human activities. This study investigated the relationship between precipitation, soil moisture, and streamflow over a wide range of watersheds across the United States using Google Earth Engine (GEE). The correlation analyses disclosed a strong association between precipitation, soil moisture, and streamflow, however, soil moisture was found to have a higher correlation with the streamflow relative to precipitation. Results indicated different strength of the association depends on the watershed classes and lag times assessments. The perennial watersheds showed higher coherence compared to intermittent watersheds. Previous month precipitation and soil moisture have a stronger influence on the current month streamflow, particularly in the snow-dominated watersheds. Monthly streamflow forecasting models were developed using an autoregressive integrated moving average (ARIMA) and support vector machine (SVM). The results showed that the SVM model generally performed better than the ARIMA model. Overall streamflow forecasting model performance varied considerably among watershed classes, and perennial watersheds tend to exhibit better predictably compared to intermittent watersheds due to lower streamflow variability. The SVM models with precipitation and streamflow inputs performed better than those with streamflow input only. Results indicated that the inclusion of antecedent root-zone soil moisture improved the streamflow forecasting in most of the watersheds, and the largest improvements occurred in the intermittent watersheds. In conclusion, this work demonstrated that knowing the relationship between precipitation, soil moisture, and streamflow in different watershed classes will enhance the understanding of the hydrologic process and can be effectively utilized in improving streamflow forecasting for better satellite-based water resource management strategies.

Nazmus Sazib↗

DOE OSTI2021

Renewable Energy for Industrial Environmental Management

Costs for renewable energy technologies have declined rapidly in the past decade and their use for residential, commercial, and utility scale electricity has grown exponentially as they become cost competitive. Simultaneously, industrial and manufacturing processes have been increasingly seeking ways to reduce emissions and operational costs in highly competitive sectors. With these combined drivers of lower cost and reduced environmental impact, renewable energy may become a viable energy provider for industrial processes such as oil and gas, mining, chemical refining, food production, and manufacturing. Renewable energy technologies may also partner with other reduced emission energy sources, such as small modular nuclear reactors and carbon capture and utilization, to create cleaner and circular industrial systems for reduced resource use. The Joint Institute for Strategic Energy Analysis (JISEA), which is a partnership of the National Renewable Energy Laboratory (NREL) and five universities and others, has been studying to potential for application of clean energy technologies to the heterogenous energy demands in industry. Dr. Jill Engel-Cox will present an overview of NREL and JISEA, the status and potential future of renewable energy technologies, and collaborations with the oil and gas industry and other industrial sectors to improve their environmental performance and reduce operational costs.

ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2015

Bundle Data Approach at GES DISC Targeting Natural Hazards

Severe natural phenomena such as hurricane, volcano, blizzard, flood and drought have the potential to cause immeasurable property damages, great socioeconomic impact, and tragic loss of human life. From searching to assessing the Big, i.e., massive and heterogeneous scientific data (particularly, satellite and model products) in order to investigate those natural hazards, it has, however, become a daunting task for Earth scientists and applications researchers, especially during recent decades. The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has served Big Earth science data, and the pertinent valuable information and services to the aforementioned users of diverse communities for years. In order to help and guide our users to online readily (i.e., with a minimum effort) acquire their requested data from our enormous resource at GES DISC for studying their targeted hazard event, we have thus initiated a Bundle Data approach in 2014, first targeting the hurricane event topic. We have recently worked on new topics such as volcano and blizzard. The bundle data of a specific hazard event is basically a sophisticated integrated data package consisting of a series of proper datasets containing a group of relevant (knowledge--based) data variables readily accessible to users via a system-prearranged table linking those data variables to the proper datasets (URLs). This online approach has been developed by utilizing a few existing data services such as Mirador as search engine; Giovanni for visualization; and OPeNDAP for data access, etc. The online Data Cookbook site at GES DISC is the current host for the bundle data. We are now also planning on developing an Automated Virtual Collection Framework that shall eventually accommodate the bundle data, as well as further improve our management in Big Data.

GES DISC↗